Call 0203 747 4615Book Appointment

AI is changing how we detect hearing loss

ByHearology Publishing | Date: Thu Jul 03 2025

Audiologist smiling while showing an older male patient the results of a hearing test on a computer screen. The man is wearing large over-ear headphones, and the screen displays an audiogram with two lines indicating hearing thresholds at different frequencies.

AI is changing how we detect hearing loss

New technologies can now identify frequency loss earlier and more accurately, particularly in older adults

Artificial intelligence is transforming audiology by helping clinicians spot frequency-specific hearing loss earlier. This is particularly important for adults over 65, many of whom gradually lose sensitivity to high frequencies. The loss of sensitivity to high frequencies is a condition known as presbycusis, and it can have a big impact on communication and quality of life.

While the average human hearing range spans from 20Hz to 20,000Hz, people often begin to lose awareness of higher frequencies above 8,000Hz in middle age. This can impair their understanding of what others are saying and their spatial awareness in noisy environments.


More than one cause

Hearing loss in older adults can be caused by age, noise exposure, or genetic predisposition. Sounds above 85dB – such as heavy traffic or loud music – are known to damage hearing over time. Clinicians increasingly recommend custom earplugs, noise-cancelling headphones, and routine hearing checks to catch deterioration early.

New AI-powered hearing aids and assistive listening systems use machine learning to adjust frequency amplification to the user’s hearing profile. These systems offer clearer sound in noisy settings and better background noise filtration, helping people follow conversations more easily in real-world environments.

“Too many people put off getting their hearing tested until the problem becomes disruptive,” said Kenny Hau, a Clinical Audiologist from Hearology®, the specialist ear health clinic. “AI and frequency mapping make it easier to get an early diagnosis, but, whilst the diagnosis is audiological, the decision to take action is psychological - and there’s nothing that AI can do about human resistance to action.

The arguments are clear - timely intervention doesn’t just protect hearing, it protects brain health too. But the real problem is the stigma associated with hearing loss. Ultimately, it’s education rather than technology that’s going to make the biggest difference in this particular space.”


Frequency mapping for early intervention

Machine learning also allows for more accurate frequency maps during diagnosis, meaning treatment can begin before more serious symptoms develop. Roughly 30% of people over 65 are affected by high-frequency hearing loss, so early testing can make a substantial difference.

As public awareness of the risks grows, more people are seeking out professional evaluations and personalised advice, whilst AI and other forms of technology continue to improve the accuracy and scope of the diagnosis. “If we are to make a breakthrough and reduce the time it takes for people with hearing loss to do something about it, we need to keep advancing on both fronts,” concludes Hau. “So that’s both education and technology.”


References